AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
This report summarizes scanner evidence for YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill, a TypeScript project with 1,872 GitHub stars. SynthScan examined 13,452 lines of code across 14 source files, recording 27 pattern matches distributed across 6 syntactic categories. The legacy adjusted pattern signal is 4.5 (Low pattern signal); it is not an authorship estimate.
Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.
Use each vector to guide manual verification of the underlying findings.
Can maintainers explain intent, assumptions, and trade-offs? 26 finding(s).
Are imports declared and package/API names verified? 1 finding(s).
Are wrappers, guards, and repeated structures necessary? 0 finding(s).
Which changes need focused human review? 27 finding(s).
This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.
Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.
This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.
The scanner identified 27 distinct pattern matches across 6 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | references/youtube-thumbnail.json | 398 | "description": "A summary of a cinematic food short video prompt, which was used to generate images in Nano Banana P | CODE |
| HIGH | references/youtube-thumbnail.json | 462 | "description": "A prompt used for image generation (Nano Banana Pro) and subsequent video generation (Kling 3.0 Omni | CODE |
| HIGH | references/youtube-thumbnail.json | 482 | "description": "A prompt, generated by GPT-5, used to create images with Nano Banana Pro that were then sequenced in | CODE |
| HIGH | references/youtube-thumbnail.json | 533 | "description": "A summarized prompt, generated by GPT-5, used for both image generation (Nano Banana Pro) and subseq | CODE |
| HIGH | references/youtube-thumbnail.json | 607 | "description": "A cinematic video prompt, generated by GPT-5 and used for Kling 3.0 Omni, describing a four-cut sequ | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | SKILL.md | 146 | ### Step 0: Auto-Update References (MANDATORY, runs every time) | COMMENT |
| LOW | SKILL.md | 172 | ### Step 1: Clarify Vague Requests | COMMENT |
| LOW | SKILL.md | 191 | ### Step 2: Search & Match | COMMENT |
| LOW | SKILL.md | 198 | ### Step 3: Present Results | COMMENT |
| LOW | SKILL.md | 272 | ### Step 4: Handle No Match (Generate Custom Prompt) | COMMENT |
| LOW | SKILL.md | 302 | ### Step 5: Remix & Personalization (Content Illustration Mode Only) | COMMENT |
| LOW | scripts/setup.js | 52 | // Step 1: Fetch manifest — discover categories dynamically | COMMENT |
| LOW | scripts/setup.js | 72 | // Step 2: Clean up stale files not in current manifest | COMMENT |
| LOW | scripts/setup.js | 83 | // Step 3: Download each category file | COMMENT |
| LOW | scripts/setup.js | 103 | // Step 4: Write timestamp | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | references/youtube-thumbnail.json | 1629 | "content": "## 1. Input Variables (Rewrite this)\nGenerate an illustration based on the following information.\n\nUs | CODE |
| MEDIUM | references/youtube-thumbnail.json | 1951 | "content": "Read the motif depicted in the attached image, generate multi-angle shots, and create four scenes divide | CODE |
| MEDIUM | references/app-web-design.json | 1821 | "content": "Luxury Korean tasting menu, editorial layout, 2+2 large grid composition, 4:5 aspect ratio.\n\nLAYOUT: 2 | CODE |
| MEDIUM | references/app-web-design.json | 2130 | "content": "# Directive (Instruction)\n**Immediately generate** a clean, modern mockup image of the highest quality | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | references/infographic-edu-visual.json | 1265 | "content": "# Instructions\nYou are a professional illustrator and prompt engineer.\nRead the following [Blog Summar | CODE |
| MEDIUM | references/infographic-edu-visual.json | 4218 | "content": "diagram:\n title: \"{argument name=\"diagram title\" default=\"The Cycle of the Generative AI Agent Dev | CODE |
| MEDIUM | references/app-web-design.json | 673 | "content": "# Instructions\nYou are a professional illustrator and prompt engineer.\nRead the following [Blog Summar | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | scripts/setup.js | 52 | // Step 1: Fetch manifest — discover categories dynamically | COMMENT |
| LOW | scripts/setup.js | 72 | // Step 2: Clean up stale files not in current manifest | COMMENT |
| LOW | scripts/setup.js | 83 | // Step 3: Download each category file | COMMENT |
| LOW | scripts/setup.js | 103 | // Step 4: Write timestamp | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | references/infographic-edu-visual.json | 2926 | "content": "Input Variable: {argument name=\"input objects\" default=\"[INSERT 1 or 2 OBJECTS]\"} \nInstruction:\nAc | CODE |